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Climate Change Social Norms and Corporate Cash Holdings

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Abstract

We study the relationship between climate change social norms (CCSN) and corporate cash holdings for U.S. firms. We find that county-level CCSN is significantly positively associated with cash holdings. Our main finding is robust to a battery of robustness tests. In a subsample analysis, we find that firms have relatively low cash holdings in low CCSN counties even when faced with high climate risk. For such firms, the lack of cash buffer could be harmful to a broader set of stakeholders faced with heightened climate risk. We also show that cash holdings are a potential mechanism through which CCSN influences future environmental corporate social responsibility (CSR) performance. Overall, our study suggests that county-level CCSN has significant implications for corporate cash holdings.

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Data availability

All data used in this paper is publicly available from the sources identified in the paper.

Notes

  1. Consistent with prior literature (e.g., Bates et al., 2009), cash accounts for roughly 26% of the total corporate assets in our sample.

  2. We describe the construction of CCSN in detail in "Measure of Climate Change Social Norms" section.

  3. Even if reverse causality is less likely to be a concern, we still conduct a test reported in the additional robustness tests in "Additional Robustness Tests" section to further eliminate this concern.

  4. Consistent with this view, Arouri and Pijourlet (2017) propose a “conflict-resolution” view stating that firms engaging in CSR are more likely to hold cash in the interests of shareholders.

  5. A central theme regarding climate change is the costs and benefits associated with climate change. Ethical issues arise when there is an attempt to address who should pay for climate adaptation and mitigation efforts (Grasso and Markowitz, 2015).

  6. One concern is that Compustat does not report firms’ historical headquarter locations. However, according to Pirinsky and Wang (2006), less than 3% of firms changed their headquarter locations over the period from 1988 to 2002. Given the shorter time span of our data (i.e., 2014–2020), corporate headquarter relocation is therefore unlikely to be a concern for our study.

  7. Please see “Appendix” for definitions of Happening, HarmUS, and Worried.

  8. Our findings remain qualitatively unchanged when standard errors are clustered at the firm level, as reported in "Additional Robustness Tests" section.

  9. It is worthwhile to note that untabulated results suggest that CCSN has not only a cross-sectional variation but also a temporal variation. Generally, there is an increasing trend in CCSN from 2014 to 2020. For instance, the proportion of respondents residing in Alabama who are concerned about global warming increased from approximately 46–56% over the sample period.

  10. We also check the variance inflation factor (VIF) for each variable and find that none of the VIFs exceed 5, mitigating the concern of multicollinearity.

  11. For the sake of brevity, the coefficients on the indicator variables on industry and year are not reported. Our results are qualitatively similar in the robustness tests when using Cash-to-assets and Cash-to-net assets as alternative dependent variables.

  12. The influence of a one-standard deviation increase in CCSN on cash holdings is calculated as: 0.050 (coefficient reported in Table 4) *1.684 (standard deviation of CCSN as reported in Table 2)/0.48 (mean of Cash as reported in Table 2) = 17.5%.

  13. Hurricane Maria is not considered here because it did not hit the U.S. mainland in 2017.

  14. See https://www.fema.gov/disaster for more details.

  15. We acknowledge that the exclusion criterion is not mathematically testable. However, it is plausible that political climate may influence CCSN through other channels such as tax laws. Therefore, certain caution should be exercised when interpreting these results (Baldauf et al., 2020).

  16. The data is sourced from https://www.c2es.org/document/climate-action-plans/.

  17. A state is considered a Democratic state if it was won by a Democratic presidential candidate in 2 of 3 presidential elections in 2008, 2012, and 2016; otherwise, we treat it as a Republican state.

  18. Former U.S. President Trump made the statement regarding the withdrawal of the U.S. from the Paris Agreement on June, 1, 2017 (see https://www.nytimes.com/2017/06/01/climate/trump-paris-climate-agreement.html for more details).

  19. The dominant political view depends on the state-level presidential elections data in 2008, 2012, and 2016. Note that we don’t use the 2020 presidential election data because it is usually deemed controversial. Our results continue to hold when we use four or five years of election results (i.e., 2000, 2004, 2008, 2012, and 2016).

  20. We thank an anonymous reviewer for raising this point.

  21. A potential drawback of this approach is that the electric vehicle data is cumulative and only available for 2020, which significantly reduces the sample size.

  22. We construct a state-level behavior-based CCSN, because responses to the question “Hear about global warming in the media at least once a week” are unavailable for 2016.

  23. Our results continue to hold if we employ a scaled decile-ranked variable.

  24. To conserve space, the cross-sectional analyses results are untabulated but available from the authors upon request.

  25. The formulas to calculate both the WW and HP indexes are listed in “Appendix”.

  26. These data are drawn from https://osf.io/fd6jq/.

  27. Relatedly, we also investigate the sources of cash holdings and we document that firms that are located in high-CCSN counties reduce their dividend payment, have a reduced likelihood to pay a dividend, and cut back net working capital and capital expenditures. We also rule out competing explanations of increased cash holdings by ruling out the tax motive, the role of R&D investment, the effect of manufacturing firms, and the agency motive. These results are unreported in the text given the space constraint but available upon request from the authors.

  28. The path coefficients are the standardized coefficients generated by path analysis automatically.

  29. Untabulated results show that the impact of CCSN on future CSR environmental performance continues to hold up to three years in the future period.

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Acknowledgments

We gratefully acknowledge helpful comments from Hao Liang (the Section Editor) and two anonymous reviewers. Kanagaretnam thanks the Social Sciences and Humanities Research Council of Canada (SSHRC) for its financial support. This project was in process when Zhang was at Schulich School of Business, York University.

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Authors and Affiliations

  1. International Business School Suzhou, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Lei Zhang

  2. Schulich School of Business, York University, Toronto, Canada

    Kiridaran Kanagaretnam

  3. International School of Economics and Management, Capital University of Economics and Business, Beijing, China

    Jing Gao

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  1. Lei Zhang
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  3. Jing Gao
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Correspondence to Jing Gao.

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Appendix: Definitions of Variables

Appendix: Definitions of Variables

Variables

Definitions

Dependent variables

 

Cash

Natural logarithm of one plus the ratio of cash and marketable securities to net assets

Cash-to-assets

The ratio of cash and marketable securities to total assets

Cash-to-net assets

The ratio of cash and marketable securities to net assets, where net assets are defined as the difference between total assets and cash and marketable securities

Cash(UDC)-to-assets

The ratio of the sum of cash, marketable securities, and unused debt capacity (UDC) to total assets, where unused debt capacity is defined as long-term debt issuance minus long-term debt reduction plus current debt changes, following Huang and Ritter (2021)

Independent variables

 

CCSN

Climate change social norms, which is constructed based on the percentages of individuals (1) “who think that global warming is happening,” (2) “who think global warming will harm people in the U.S. a moderate amount/a great deal,” and (3) “who are somewhat/very worried about global warming.” Our measure of CCSN is derived by using principal component analysis extracting the first principal component

EVU

The number of electric vehicle registration at the state level

CCSNB

An alternative measure of climate change social norms, which is constructed based on the percentages of individuals who (1) “Discuss global warming at least occasionally,” and (2) “Hear about global warming in the media at least once a week.” Our measure of CCSNB is derived by using principal component analysis extracting the first principal component

MCCSN

The arithmetic average of the percentages of individuals who give positive responses to the three interview questions

CCSN5

Scaled quintile rank of CCSN

S-CCSN

The measure of CCSN constructed at the state level

Happening

The percentage of respondents “who think that global warming is happening”

HarmUS

The percentage of respondents “who think global warming will harm people in the U.S. a moderate amount/a great deal”

Worried

The percentage of respondents “who are somewhat/very worried about global warming?”

Control variables

 

Size

Natural logarithm of total assets

MTB

The market value of equity divided by the book value of equity

Lev

Long-term debt plus debt in current liabilities, scaled by total assets

CF

Cash flow from operations scaled by total assets

CF_sd

The volatility of cash flows, measured as the standard deviation of cash flow over the past four years

Nwc

The difference between working capital and cash holdings, scaled by total assets

Divi

An indicator variable equal to one if the firm paid dividends during the year and zero otherwise

RD

Research and development expenses scaled by total assets, set to zero if the R&D expenditures are missing in Compustat

Capx

Capital expenditures scaled by total assets

Aqc

Acquisition expenses scaled by total assets

Affected

An indicator variable equal to one if a major natural disaster hits a county in a given year ± 2 years, and zero otherwise

Post

An indicator variable equal to one in 2018–2020 and zero in 2014–2016

Neighbor

An indicator variable equal to one if the firm is headquartered in the neighboring states of a state hit by Hurricanes Harvey or Irma and zero otherwise

D(t = − 1)

An indicator variable equal to one for 2016 and zero otherwise

D(t = − 2)

An indicator variable equal to one for 2015 and zero otherwise

D(t = − 3)

An indicator variable equal to one for 2014 and zero otherwise

D(t = 1)

An indicator variable equal to one for 2018 and zero otherwise

D(t = 2)

An indicator variable equal to one for 2019 and zero otherwise

D(t = 3)

An indicator variable equal to one for 2020 and zero otherwise

Repubpp

The percentage of individuals in a ZIP code voting for a Republican Party candidate

CAP

An indicator variable equal to one if a state has CAPs in place or is in the process of designing one and zero otherwise

AvgCCSN

Average county-level CCSN within a state (excluding the focal county)

WW

An indicator variable equal to one if the firm’s WW index is above the sample median, and zero otherwise. Whited and Wu (WW) (2006) index is calculated as: 0.091CF − 0.0.062DIVPOS + 0.021TLTD − 0.0.044LNTA + 0.102ISG- 0.035SG, where CF is cash flow scaled by total assets, DIVPOS is a dummy variable which equals one if the firm pays dividends, TLTD is total long-term debt divided by total assets, LNTA is the natural logarithm of total assets, ISG is average industry sales growth at the 3 digit SIC level and SG is the change of sales per year

HP

An indicator variable equal to one if the firm’s HP index is above the sample median, and zero otherwise. Hadlock and Pierce (HP) (2010) index is calculated as: − 0.737SIZE + 0.043*SIZE2 − 0.040AGE. where SIZE is natural logarithm of total assets, and AGE is the number of years the firm has been listed on Compustat

Media

An indicator variable equal to one if the media coverage of climate uncertainty is greater than the sample median and zero otherwise. Media coverage is calculated as the frequency of articles containing the following duo of terms: “climate change” or “global warming” and “uncertain” or “uncertainty” using The Wall Street Journal

Expo

An indicator variable equal to one if a firm’s climate risk exposure is greater than the median during the year and zero otherwise

Lat

The latitude of a county

Lng

The longitude of a county

Fepp

The proportion of female population in a county

GDP

County-level per capita GDP

College

The percentage of the population (age 25 and above) who earned a college degree or higher

Political

An indicator variable equal to one if a state was won by a Democratic presidential candidate in 2 of 3 presidential elections in 2008, 2012, and 2016, and zero otherwise

Escore

CSR environmental performance score obtained from Sustainalytics

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Zhang, L., Kanagaretnam, K. & Gao, J. Climate Change Social Norms and Corporate Cash Holdings. J Bus Ethics 190, 661–683 (2024). https://doi.org/10.1007/s10551-023-05440-x

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